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Add long-term memory to OpenClaw agents with the @mem0/openclaw-mem0 plugin. Your agent forgets everything between sessions — this plugin fixes that by automatically watching conversations, extracting what matters, and bringing it back when relevant.

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Overview

OpenClaw Mem0 Architecture
The plugin provides:
  1. Auto-Recall — Before the agent responds, memories matching the current message are injected into context
  2. Auto-Capture — After the agent responds, the exchange is sent to Mem0 which decides what’s worth keeping
  3. Agent Tools — Five tools for explicit memory operations during conversations
Both auto-recall and auto-capture run silently with no manual configuration required.

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Installation

openclaw plugins install @mem0/openclaw-mem0

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Setup and Configuration

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Understanding userId

The userId field is a string you choose to uniquely identify the user whose memories are being stored. It is not something you look up in the Mem0 dashboard — you define it yourself. Pick any stable, unique identifier for the user. Common choices:
  • Your application’s internal user ID (e.g. "user_123", "[email protected]")
  • A UUID (e.g. "550e8400-e29b-41d4-a716-446655440000")
  • A simple username (e.g. "alice")
All memories are scoped to this userId — different values create separate memory namespaces. If you don’t set it, it defaults to "default", which means all users share the same memory space.
In a multi-user application, set userId dynamically per user (e.g. from your auth system) rather than hardcoding a single value.

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Platform Mode (Mem0 Cloud)

Get your API key from app.mem0.ai.
Add to your openclaw.json: 
// plugins.entries
"openclaw-mem0": {
  "enabled": true,
  "config": {
    "apiKey": "${MEM0_API_KEY}",
    "userId": "alice"  // any unique identifier you choose for this user
  }
}

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Open-Source Mode (Self-hosted)

No Mem0 key needed. Requires OPENAI_API_KEY for default embeddings/LLM. 
"openclaw-mem0": {
  "enabled": true,
  "config": {
    "mode": "open-source",
    "userId": "alice"  // any unique identifier you choose for this user
  }
}
Sensible defaults work out of the box. To customize the embedder, vector store, or LLM: 
"config": {
  "mode": "open-source",
  "userId": "your-user-id",
  "oss": {
    "embedder": { "provider": "openai", "config": { "model": "text-embedding-3-small" } },
    "vectorStore": { "provider": "qdrant", "config": { "host": "localhost", "port": 6333 } },
    "llm": { "provider": "openai", "config": { "model": "gpt-4o" } }
  }
}
All oss fields are optional. See Mem0 OSS docs for available providers.

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Short-term vs Long-term Memory

Memories are organized into two scopes:
  • Session (short-term) — Auto-capture stores memories scoped to the current session via Mem0’s run_id / runId parameter. These are contextual to the ongoing conversation.
  • User (long-term) — The agent can explicitly store long-term memories using the memory_store tool (with longTerm: true, the default). These persist across all sessions for the user.
During auto-recall, the plugin searches both scopes and presents them separately — long-term memories first, then session memories — so the agent has full context.

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Agent Tools

The agent gets five tools it can call during conversations:
ToolDescription
memory_searchSearch memories by natural language
memory_listList all stored memories for a user
memory_storeExplicitly save a fact
memory_getRetrieve a memory by ID
memory_forgetDelete by ID or by query
The memory_search and memory_list tools accept a scope parameter ("session", "long-term", or "all") to control which memories are queried. The memory_store tool accepts a longTerm boolean (default: true) to choose where to store.

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CLI Commands

# Search all memories (long-term + session)
openclaw mem0 search "what languages does the user know"

# Search only long-term memories
openclaw mem0 search "what languages does the user know" --scope long-term

# Search only session/short-term memories
openclaw mem0 search "what languages does the user know" --scope session

# View stats
openclaw mem0 stats

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Configuration Options

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General Options

KeyTypeDefaultDescription
mode"platform" | "open-source""platform"Which backend to use
userIdstring"default"Scope memories per user
autoRecallbooleantrueInject memories before each turn
autoCapturebooleantrueStore facts after each turn
topKnumber5Max memories per recall
searchThresholdnumber0.3Min similarity (0–1)

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Platform Mode Options

KeyTypeDefaultDescription
apiKeystring—Required. Mem0 API key (supports ${MEM0_API_KEY})
orgIdstring—Organization ID
projectIdstring—Project ID
enableGraphbooleanfalseEntity graph for relationships
customInstructionsstring(built-in)Extraction rules — what to store, how to format
customCategoriesobject(12 defaults)Category name → description map for tagging

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Open-Source Mode Options

KeyTypeDefaultDescription
customPromptstring(built-in)Extraction prompt for memory processing
oss.embedder.providerstring"openai"Embedding provider ("openai", "ollama", etc.)
oss.embedder.configobject—Provider config: apiKey, model, baseURL
oss.vectorStore.providerstring"memory"Vector store ("memory", "qdrant", "chroma", etc.)
oss.vectorStore.configobject—Provider config: host, port, collectionName, dimension
oss.llm.providerstring"openai"LLM provider ("openai", "anthropic", "ollama", etc.)
oss.llm.configobject—Provider config: apiKey, model, baseURL, temperature
oss.historyDbPathstring—SQLite path for memory edit history
Everything inside oss is optional — defaults use OpenAI embeddings (text-embedding-3-small), in-memory vector store, and OpenAI LLM.

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Key Features

  1. Zero Configuration — Auto-recall and auto-capture work out of the box with no prompting required
  2. Dual Memory Scopes — Session-scoped short-term and user-scoped long-term memories
  3. Flexible Backend — Use Mem0 Cloud for managed service or self-host with open-source mode
  4. Rich Tool Suite — Five agent tools for explicit memory operations when needed

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Conclusion

The @mem0/openclaw-mem0 plugin gives OpenClaw agents persistent memory with minimal setup. Whether using Mem0 Cloud or self-hosting, your agents can now remember user preferences, facts, and context across sessions automatically.

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